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This repository has been archived by the owner on Jul 16, 2024. It is now read-only.
Hi,
For multi objective problems with non linear constraints, can we run the algorithms directly without framing the nonlinear constraints into the problem definition?
I am getting this error message when trying: (with moead, i got similar messages). Any help is appreciated. Thanks
ps-Sorry about the formatting, somehow the code insertion only recognizes part of the code
function: evolve
where: C:\bld\pygmo_1495138803255\work\pagmo2-2.3\include\pagmo/algorithms/nsga2.hpp, 145
what: Non linear constraints detected in pygmo-test problem instance. NSGA-II cannot deal with them.
`<import pygmo as pg
class myProb:
def init(self, dim):
self.dim = dim
Hi,
For multi objective problems with non linear constraints, can we run the algorithms directly without framing the nonlinear constraints into the problem definition?
I am getting this error message when trying: (with moead, i got similar messages). Any help is appreciated. Thanks
ps-Sorry about the formatting, somehow the code insertion only recognizes part of the code
function: evolve
where: C:\bld\pygmo_1495138803255\work\pagmo2-2.3\include\pagmo/algorithms/nsga2.hpp, 145
what: Non linear constraints detected in pygmo-test problem instance. NSGA-II cannot deal with them.
`<import pygmo as pg
class myProb:
def init(self, dim):
self.dim = dim
probMy = pg.problem(myProb(3))
algo = pg.algorithm(pg.moead(gen = 1))
#algo = pg.algorithm(pg.nsga2(gen = 1))
pop = pg.population(probMy, 10*4)
result = algo.evolve(pop)`
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